torch.nn.functional.avg_pool1d

torch.nn.functional.avg_pool1d(input, kernel_size, stride=None, padding=0, ceil_mode=False, count_include_pad=True) → Tensor

对由多个输入平面组成的输入信号进行1D平均池化操作。

注意

padding 最多应该是有效核大小的一半。

See AvgPool1d for details and output shape.

参数

• input – input tensor of shape $(\text{minibatch} , \text{in\_channels} , iW)$

• kernel_size – the size of the window. Can be a single number or a tuple (kW,)

• stride – the stride of the window. Can be a single number or a tuple (sW,). Default: kernel_size

• padding – implicit zero paddings on both sides of the input. Can be a single number or a tuple (padW,). Default: 0

• ceil_mode – when True, will use ceil instead of floor to compute the output shape. Default: False

• count_include_pad – when True, will include the zero-padding in the averaging calculation. Default: True

示例

>>> # pool of square window of size=3, stride=2
>>> input = torch.tensor([[[1, 2, 3, 4, 5, 6, 7]]], dtype=torch.float32)
>>> F.avg_pool1d(input, kernel_size=3, stride=2)
tensor([[[ 2.,  4.,  6.]]])